Ridge regression and artificial neural network to predict the thermodynamic properties of alkali metal Rankine cycles for space nuclear power-Reference-Cited by-同舟云学术

Ridge regression and artificial neural network to predict the thermodynamic properties of alkali metal Rankine cycles for space nuclear power

Published:2022-12 Issue: Volume:273 Page:116385
ISSN:0196-8904
Container-title:Energy Conversion and Management
language:en
Short-container-title:Energy Conversion and Management

Author:

Sun Qi-qi,Zhang Hao-Chun,Sun Zi-jian,Xia Yan

Funder

National Key Research and Development Program of China

Publisher

Elsevier BV

Subject

Energy Engineering and Power Technology,Fuel Technology,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment

Reference64 articles.

1. Developments in sodium technology;Kale;Curr Sci,2004

2. Alchagirov BB, Khokonov KB. Alkali metals and their alloys are perspective materials of modern techniques and power engineering. In: Proceedings of the Physics and Chemistry of Perspective Materials: The Collection of the Proceedings, Kabardino-Balkarian State University KBSU, Nalchik, 1998, p. 40.

3. Liquid metallic coolant in the thermal pipes and energy devices;Bistrov,1988

4. Technology for large Rankine cycle space power systems;Zipkin;J Spacecraft Rockets,1966

5. Comparative thermoeconomic analysis of geothermal energy recovery via super/transcritical CO2 and subcritical organic Rankine cycles;Habibollahzade;Energy Convers Manage,2022

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